caseSHY/aicoreutils
AICoreUtils is a JSON-first, LLM-agent-friendly CLI toolkit exposing ~114 utilities inspired by GNU Coreutils via MCP, with structured JSON output, dry-run support, overwrite protection, and stable exit codes.
File & Directory Operations
ls, cat, cp, mv, rm, mkdir, touch, stat, ln, readlink, realpath, mktemp, install, mkfifo, mknod — with dry-run, overwrite protection, and bounded output.
Text Processing
head, tail, sort, cut, tr, paste, join, comm, nl, tac, fmt, fold, expand, pr, od, split, csplit, ptx, shuf, tee, wc.
Hashing & Checksums
md5sum, sha1/224/256/384/512sum, b2sum, cksum, sum — compute cryptographic hashes and checksums.
Encoding & Conversion
base32, base64, basenc (base16/64url), numfmt (SI/IEC units), seq.
System & Environment
env, printenv, pwd, date, uname, arch, hostname, hostid, id, groups, logname, whoami, pinky, nproc, df, du, sync.
Process & Execution
timeout, nice, nohup, kill, stdbuf, sleep (capped at 60s), chroot, runcon — with explicit confirmation for destructive/privileged operations.
Permissions & Ownership
chmod, chown, chgrp, chcon (SELinux).
Expressions & Logic
test/[, expr, factor, true, false, echo, printf, basename, dirname, pathchk.
Agent & Meta Tools
tool-list— export tool definitions in aicoreutils, OpenAI, or Anthropic function-calling formatsschema— print the full JSON protocol and exit codescatalog— list prioritized Coreutils categories for agentscoreutils— list or describe the full command surface
Key Design Principles
All output defaults to JSON;
--rawavailable for plain text pipingErrors reported as structured JSON with stable exit codes
--dry-runon destructive commands; explicit--allow_overwriteflagsBounded output for security and resource management
Native MCP integration for Claude Desktop and compatible agent frameworks
Provides OpenAI Function Calling format output via tool-list --format openai, enabling integration with any Agent framework that supports function calling.
AICoreUtils
Glama 92% | TDQS A 级 (均值 4.6) | 114 工具全部 A 级 | CI 全平台通过 | Production/Stable
🤖 MCP 目录已收录:Glama · ModelScope · awesome-mcp-servers
中文说明
AICoreUtils 是一个面向 LLM Agent 的 JSON 优先命令行工具包原型。它参考 GNU Coreutils 的常用命令,但不是完整的 GNU 兼容替代品。
项目目标是给机器调用方提供确定、低噪音、易解析的 CLI 接口:
默认输出 JSON
错误以 JSON 写入 stderr
退出码语义稳定
修改文件的命令支持
--dry-run需要管道组合时显式使用
--raw
快速开始
pip install aicoreutils
aicoreutils schema --pretty
aicoreutils ls . --limit 20
aicoreutils rm build --recursive --dry-run🤖 Claude Desktop / MCP 集成
一行配置,让 Claude 直接操作你的文件系统:
编辑 Claude Desktop 配置文件(详细说明 →):
系统 | 配置文件 |
macOS |
|
Windows |
|
Linux |
|
{
"mcpServers": {
"aicoreutils": {
"command": "python",
"args": ["-m", "aicoreutils.mcp_server"]
}
}
}重启 Claude Desktop,然后对它说:
"列出项目里所有 Python 文件,统计代码行数"
Claude 自动调用 aicoreutils ls + aicoreutils wc,全程 JSON 交互。
更多集成方式:aicoreutils tool-list --format openai 输出 OpenAI Function Calling 格式,可直接用于任意 Agent 框架。
如需给调度器或审计系统保留风险标签,可追加 --include-risk。
⚠️ 安全提示:生产环境建议以最低权限运行。
aicoreutils-mcp --profile readonly # 推荐:只读工具 aicoreutils-mcp --profile workspace-write # 仅允许低风险 cwd 内写入详见 生产安全部署指南 →
🤖 AI IDE 集成
在 Cursor / Windsurf / Continue.dev 中直接使用 aicoreutils:AI IDE 集成指南 →
// ~/.cursor/mcp.json
{ "mcpServers": { "aicoreutils": { "command": "python", "args": ["-m", "aicoreutils.mcp_server"] } } }🔗 更多:Claude Desktop 集成 | AI IDE 集成 | Agent 任务示例 | LangChain 包装器
运行测试
# 推荐主入口(pytest,含 Hypothesis property-based 测试和 GNU 对照测试)
uv run pytest tests/ -v --tb=short
# Legacy 入口(unittest,部分运行器)
uv run python -m unittest discover -s tests -v项目结构
.
|-- src/aicoreutils/ # Python 包源码
|-- docs/ # 文档入口
| |-- reference/ # 协议、命令面和安全生产契约
| |-- guides/ # 使用指南
| |-- architecture/ # 架构决策记录 (ADR) 和 AI 代理规则
| |-- development/ # 测试和开发说明
| |-- status/ # 当前项目状态(唯一权威来源)
| |-- audits/ # 兼容性和质量审计
| |-- analysis/ # 项目分析日志(历史归档)
| `-- reports/ # 测试报告等生成/归档文档
|-- tests/ # 测试套件
|-- examples/ # 示例
|-- scripts/ # CI/审计/发布脚本
|-- .github/ # CI workflows 和 issue 模板
`-- vendor/ # 本地上游源码缓存文档
发布状态
当前实现:aicoreutils schema 中登记 114 个 CLI 命令(含 tool-list 等 Agent 元命令)。
重要限制:本项目是受 GNU Coreutils 启发的 Agent 友好子集,不是完整的 GNU Coreutils 克隆。
English
AICoreUtils is a JSON-first command-line toolkit prototype for LLM agents. It is inspired by common GNU Coreutils commands, but it is not a complete GNU-compatible replacement.
The goal is a deterministic, low-noise interface for machine callers:
JSON output by default
JSON errors on stderr
Stable semantic exit codes
--dry-runfor mutation commandsExplicit
--rawoutput for pipeline composition
Quick Start
pip install aicoreutils
aicoreutils schema --pretty
aicoreutils ls . --limit 20
aicoreutils rm build --recursive --dry-run🤖 Claude Desktop / MCP Integration
One config line to let Claude operate your filesystem:
Edit Claude Desktop config (full guide →):
OS | Config File |
macOS |
|
Windows |
|
Linux |
|
{
"mcpServers": {
"aicoreutils": {
"command": "python",
"args": ["-m", "aicoreutils.mcp_server"]
}
}
}Restart Claude Desktop, then ask:
"List all Python files in the project and count lines of code"
Claude calls aicoreutils ls + aicoreutils wc automatically.
For other frameworks: aicoreutils tool-list --format openai outputs OpenAI Function Calling format directly.
Add --include-risk when an orchestrator or audit system needs machine-readable risk metadata.
⚠️ Security: Run with least privilege in production.
aicoreutils-mcp --profile readonly # Recommended: read-only tools aicoreutils-mcp --profile workspace-write # Low-risk cwd-local writes only
Run tests
# Recommended primary entry (pytest, includes Hypothesis property-based and GNU differential tests)
uv run pytest tests/ -v --tb=short
# Legacy entry (unittest, partial runner)
uv run python -m unittest discover -s tests -vProject Layout
.
|-- src/aicoreutils/ # Python package
|-- docs/ # documentation index
| |-- reference/ # protocol, command-surface and security contracts
| |-- guides/ # usage guides
| |-- architecture/ # ADRs and AI agent governance rules
| |-- development/ # testing and development notes
| |-- status/ # current project status (single authoritative source)
| |-- audits/ # compatibility and quality audits
| |-- analysis/ # project analysis logs (historical archive)
| `-- reports/ # test reports and archived generated docs
|-- tests/ # test suite
|-- examples/ # examples
|-- scripts/ # CI/audit/release scripts
|-- .github/ # CI workflows and issue templates
`-- vendor/ # local upstream source cacheDocumentation
Current project status ← authoritative status source
Release Status
Current implementation: 114 CLI commands in aicoreutils schema (including agent-native meta-commands like tool-list).
Important limitation: this project is an agent-friendly subset inspired by GNU Coreutils, not a full GNU Coreutils clone.
稳定性和 SemVer
aicoreutils 从 v1.0.0 起采用语义化版本控制,承诺如下:
Patch (1.0.x):修复 bug、改进错误消息、补充文档。JSON 输出结构不变。
Minor (1.x.0):新增命令、新增参数。已有命令的 JSON 输出结构保持向后兼容。
Major (x.0.0):破坏性变更 — JSON schema 变化、命令重命名、MCP tool schema 变化。
⚠️ Stability note: JSON envelope (ok, result, error, command, version), MCP tool schema, and semantic exit codes are stable. Production use: pin the version (pip install aicoreutils==1.2.2). v1.2.2 LTS — critical bug and security fixes backported for at least 12 months. CLI internal argument parsing may evolve across minor versions. See Stability & SemVer.
Maintenance
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